Publications

IS&T Int’l Sym. A: Article, B: Book Chapter, C: Conference Proceeding, J: Journal, P: Patent, R: Technical Report, CR: Consultation Report, T: Thesis

After 2013: 9 journals, 13 conference proceedings

[Computer Vision: Surface Defect Detection]

  1. (J) H.Y.T. Ngan, G.K.H. Pang, S.P. Yung and M.K. Ng, “Wavelet based methods on Patterned Fabric Defect Detection,” Pattern Recognition, vol. 38, issue 4, pp. 559-576, 2005.
  2. (J) H.Y.T. Ngan and G.K.H. Pang, “Novel Method for Patterned Fabric Inspection using Bollinger Bands,” Optical Engineering, vol. 45, no. 8, 2006.
  3. (J) H.Y.T. Ngan and G.K.H. Pang, “Regularity Analysis for Patterned Texture Inspection,” IEEE Trans. Automation Science & Engineering, vol. 6, no. 1, pp. 131-144, 2009. 
  4. (J) H.Y.T. Ngan, G.K.H. Pang and N.H.C. Yung, “Motif-based Defect Detection for Patterned Fabric,” Pattern Recognition, vol. 41, issue 6, pp. 1878-1894, 2008. (Times cited: 31) [~Accepted with minor revisions]
  5. (J) H.Y.T. Ngan, G.K.H. Pang and N.H.C. Yung, “Performance Evaluation for Motif-based Patterned Texture Defect Detection,” IEEE Trans. Automation Science & Engineering, vol. 7, no. 1, pp. 58-72, 2010. 
  6. (J) H.Y.T. Ngan, G.K.H. Pang and N.H.C. Yung, “Ellipsoidal Decision Regions for Motif-based Patterned Fabric Defect Detection,” Pattern Recognition, vol. 43, no. 6, pp. 2132-2144, 2010. 
  7. (J) H.Y.T. Ngan, G.K.H. Pang and N.H.C. Yung, “Automated Fabric Defect Detection – A Review,” Image and Vision Computing, vol. 29, no. 7, pp. 442-458, 2011 . [In the list of recently published articles from most cited Image and Vision Computing Articles within 2011-2016: 12 Jun, 2015]
  8. (J) H.Y.T. Ngan and G.K.H. Pang, “Robust Defect Detection in Plain and Twill Fabric Using Directional Bollinger Bands,” Optical Engineering, vol. 54, no. 7, 073106, 2015. doi:10.1117/1.OE.54.7.073106.
  9. (J) M.K. Ng, H.Y.T. Ngan, X. Yuan and W. Zhang,”Patterned Fabric Inspection and Visualization by the Method of Image Decomposition,” IEEE Trans.  Automation Science & Engineering, vol. 11, no. 3, pp. 943-947, 2014.
  10. (J) C.S.C. Tsang, H.Y.T. Ngan and G.K.H. Pang, “Fabric Inspection based on the ELO Rating Method,” Pattern Recognition, vol. 51, pp. 378-394, 2016.
  11. (J) W.Y. Chan, H.Y.T. Ngan, G.K.H. Pang, M.K. Ng, “Patterned Fabric Defect Detection by Rotational Bollinger Bands” (Submitted).
  12. (J) M.K. Ng, H.Y.T. Ngan, X. Yuan and W. Zhang, “Lattice-based Patterned Fabric Inspection by Using Total Variation and Sparsity with Low-Rank Representations” SIAM Journal on Imaging Sciences (Accepted).
  13. (C) C.C.W. Chan, W. Zhang, H.Y.T. Ngan, “Rotational Regular Bands for Patterned Fabric Inspection” (Submitted).
  14. (C) H.Y.T. Ngan, G.K.H. Pang, S.P. Yung, and M. K. Ng, “Defect Detection on Patterned Jacquard Fabric,” IEEE Int’l Workshop on 32nd Applied Imagery Pattern Recognition (AIPR2003), Washington DC, US, pp.163-168, 15-17 Oct, 2003.  (poster)
  15. (C) H.Y.T. Ngan, and G.K.H. Pang, “Comparison on Methods for Defect Detection of Patterned Jacquard Fabric,” Proc. Int’l Sym. Collaborative Research in Applied Science (ISOCRIAS2005), UBC, Vancouver, Canada, pp. 134-141, 7-9 Oct, 2005. (oral)
  16. (C) H.Y.T. Ngan, G.K.H. Pang and N.H.C. Yung, “Patterned Fabric Defect Detection Using A Motif-based Approach,” Proc. IEEE Int’l Conference on Image Processing (ICIP2007), San Antonio, Texas, US, vol.2, pp. II-33-II-36, 16-19 Sep, 2007. (oral)
  17. (B) H.Y.T. Ngan and G.K.H. Pang, “Defect Detection on Patterned Objects,” MECHATRONIC SYSTEMS-Devices, Design, Control, Operation, and Monitoring, Taylor & Francis, CRC Press, p. 24/1-24/10, 2007.
  18. (T) H.Y.T. Ngan, “Patterned Jacquard Fabric Defect Detection,” M.Phil. Thesis, The University of Hong Kong, 2004. (http://hub.hku.hk/handle/10722/32188 , downloaded 976 times in HKU Scholar Hub up to August 30, 2013)
  19. (T) H.Y.T. Ngan, “Motif-based Method For Patterned Texture Defect Detection,” Ph.D. Thesis, The University of Hong Kong, 2008. (http://hub.hku.hk/handle/10722/51501 , downloaded 982 times in HKU Scholar Hub up to August 30, 2013)

[Social Signal Processing: Social Group & Crowd Behavior, Digital Social Science]

  1. (J) H.Y.T. Ngan, L. Wang, C.Y. Liu, J.Qin and N.H.C. Yung, “A Framework of Multi-layer Visual Surveillance on Humans and Vehicles,” IEEE Trans. (In preparation).
  2. (J) H.Y.T. Ngan, L. Wang, Z. Chen and N.H.C. Yung, “Social Group Discovery via Two-level Social Network,” IEEE Trans. (In preparation).
  3. (C) H.Y.T. Ngan, L. Wang and N.H.C. Yung, “Social Group Discovery via Two-level Social Network,” Proc. IEEE 3rd Int’l Conf. Power Electronics & Intelligent Transportation System (PEITS), Shenzhen, China, vol. IV, pp. 196-199, 20-21Nov, 2010. (oral)
  4. (C) H.Y.T. Ngan, Z. Chen and N.H.C. Yung, “Social Group Discovery of Human Motion Patterns via Two-level Social Network,” (In preparation).
  5. (C) H.Y.T. Ngan, H. Kawai, K. Kunieda, K. Yamada, “Social Behavior Analysis in Visual Human Monitoring System: A Survey and Perspective,” arXiv:1607.06219.
  6. (C) C.C.W. Chan, K.S. Li, H.Y.T. Ngan, “Weaving Pattern Recognition of Ancient Chinese Textiles by Regular Bands Analysis,” IS&T Int’l Sym. Electronic Imaging, no. 6, pp. 31-36, 2017 (oral).
  7. (R) H.Y.T. Ngan, “Human Motion Analysis for Social Behavior in Visual Surveillance,” NEC Research Report, 31 Mar, 2009.
  8. (R) H.Y.T. Ngan, “Corpus Construction for Multi-modal Visual Surveillance in CCIL,” NEC Research Report, 11 Sep, 2009.

[Smart Cities: Large-scale Traffic Behavior Analysis]

  1. (J) H.Y.T. Ngan, N.H.C. Yung and A.G.O. Yeh, “Detection of Outliers in Traffic Data based on Dirichlet Process Mixture Model,”  IET Intelligent Transportation Systems, vol. 9, no. 7, pp. 773-781, 2015.
  2. (J) H.Y.T. Ngan, N.H.C. Yung and A.G.O. Yeh, “Performance Evaluation of Various Outlier Detection Methods in Traffic Data,” (In preparation).
  3. (J) L. Wang, H.Y.T. Ngan and N.H.C. Yung, “Automatic Incident Classification for Large-scale Traffic Data by Adaptive Boosting SVM,” (Submitted).
  4. (J) J. Tang and H.Y.T. Ngan, “Traffic Outlier Detection by Density-based Bounded Local Outlier Factors,” IT in Industry, vol. 4, no. 1, pp. 6-18, 2016  [Invited for publication].
  5. (J) C.H.M. Wong, H.Y.T. Ngan, N.H.C. Yung, A.W.-C. Liew, “A Novel Node-based Modulo-K Clustering Tree for Automatic Traffic Incident Classification,” (Submitted).
  6. (C) X. Lan, W. Liu and H.Y.T. Ngan, “Joint 4-D DOA and Polarization Estimation Based on Linear Tripole Arrays,” Proc. IEEE Int’l Conf. DSP 2017 (Accepted).
  7. (C) L-L. Wang, H.Y.T. Ngan, W. Liu and N.H.C. Yung, “Anomaly Detection for Quaternion-valued Traffic Signals,” Proc. IEEE DICTA, 2016 (poster).
  8. (C) C.H.M. Wong, H.Y.T. Ngan and N.H.C. Yung, “Modulo-k Clustering based Outlier Detection for Large-scale Traffic Data,” Proc. Int’l Conf. IEEE Information Technology and Application (ICITA), 2016. (oral)
  9. (C) P. Lam, L. Wang, H.Y.T. Ngan, N.H.C. Yung and A.G.O. Yeh, “Outlier Detection in Large-scale Traffic Data by Naïve Bayes Method and Gaussian Mixture Model Method,” IS&T Int’l Sym. Electronic Imaging, no. 6, pp. 73-78, 2017. (oral)
  10. (C) K.P.K. Tang and H.Y.T. Ngan, “Robust Vehicle Edge Detection by Cross Filter Method,” IEEE AIPR Workshop, pp. 1-7, 2014(poster)
  11. (C) H.Y.T. Ngan, N.H.C. Yung, and A.G.O. Yeh, “A Comparative Study of Outlier Detection for Large-scale Traffic Data by One-class SVM and Kernel Density Estimation,” IS&T/SPIE Electronic Imaging, 94050I-94050I-10, 2015 . (oral)
  12. (C) T.T. Dang, H.Y.T. Ngan, W.Liu, “Distance-based k-nearest Neighbors Outlier Detection Method in Large-scale Traffic Data,” Proc. IEEE Int’l Conf. Digital Signal Processing (DSP), pp. 507-510, 2015. (oral)
  13. (C) H.Y.T. Ngan, N.H.C. Yung, and A.G.O. Yeh, “Modeling of Traffic Data based by Dirichlet Process Mixtures,” 8th IEEE Int’l Conf. Automation Science & Engineering (CASE), pp. 224-229, 2012. (oral)
  14. (C) M.X. Ma, H.Y.T. Ngan, W.Liu, “Density-based Outlier Detection Method by Local Outlier Factor on Large-scale Traffic Video Data,” IS&T Int’l Sym. Electronic Imaging, no. 4, pp. 1-4, 2016.  (oral)
  15. (CR) H.Y.T. Ngan and N.H.C. Yung, “Report for Traffic Behavior Analysis at The Junction of Chatham Road South, Austin Road & Cheong Wan Road,” HKU Versitech Ltd., 303 pages, 2011.

[Medical Imaging: Dental Implant Technology]

  1. (C) W.Y.H. Lam, H.Y.T. Ngan, P.Y.P. Wat, H.W.K. Luk, E.H.N. Pow, T.K. Goto, “Novel Geometric Coordination Registration in Cone-beam Computed Tomogram,” IEEE AIPR Workshop, pp. 1-6, 2014. (oral)
  2. (C) W.Y.H. Lam, H.Y.T. Ngan, P.Y.P. Wat, H.W.K. Luk, E.H.N. Pow, T.K. Goto, “Image Calibration and Registration in Cone-beam Computed Tomogram for Measuring the Accuracy of Computer-aided Implant Surgery,” IS&T/SPIE Electronic Imaging, 94050A-94050A-12, 2015(oral)
  3. (C) W.Y.H. Lam, H.Y.T. Ngan, R. Hsung, P.Y.P. Wat, H.W.K. Luk, E.H.N. Pow, T.K. Goto, “Using Intra-oral Scanner to Evaluate Implant Position,” 29th Annual Scientific Meeting of the Int’l Association of the Dental Research Southeast Asia Division (IADR-SEA), 2015. (oral)
  4. (C) W.Y.H. Lam, H.Y.T. Ngan, R. Hsung, P.Y.P. Wat, H.W.K. Luk, E.H.N. Pow, T.K. Goto, “Validation of a Novel Geometric Coordination Registration using Manual and Semi-automatic Methods in Cone-beam Computed Tomogram,” IS&T Int’l Sym. Electronic Imaging, no. 6, pp. 1-6, 2016 (oral).
  5. (P) W.Y.H. Lam, H.Y.T. Ngan, R. Hsung, H.W.K. Luk, E.H.N. Pow, US Patent, 2016 (pending).

[Others]

  1. (A) 顏旭東 (2001) 書評,”從<<成佛之道>>看戒律”  [pdf]. (unpublished)

Remarks:

a. According to JCR Science Citation Index 2010, the 5-year impact factors (IF) of the journals are listed below.

IEEE Trans. Automation Science & Engineering (5-year IF= 2.763) [16% acceptance rate]

Pattern Recognition (5-year IF= 3.707) [21% acceptance rate]

Image and Vision Computing (5-year IF = 2.583) [13% acceptance rate]

Optical Engineering (5-year IF = 0.908

IET Intelligent Transportation Systems (5-year IF = 1.277)

b. Acceptance rates are informed by the journal publishers or Editor-in-Chief.
IEEE Transactions on Automation Science & Engineering is ranked number 3 of among Automation Journals by the h5 citation index. Journals of Pattern Recognition, and Image and Vision Computing are the grade A journals and ranked within the top 20% in the area of computer vision and pattern recognition.

c. Information on Times cited is retrieved from Google Scholar.

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